Recent progress in computer vision makes it possible to reconstruct clothing shape from a single-view input, which allows a much simpler capture setup. A monocular video was used to recover cloth simulation parameters in [1]}, and this system was improved to also estimate the 2D cloth pattern from a single image in [2]}. More recently, one line of work treats the problem as a monocular 3D shape regression task with explicit [3]}, [4]} or implicit [5]}, [6]}, [7]}, [8]}, [9]}, [10]} shape representation. Alternatively, optimization-based [11]}, [12]}, [13]} or learning-based approaches [14]}, [15]} are used to deform a personalized template shape to match the input image. Most of these methods only focus on estimating clothed body shape without photorealistic texture (except [7]}). In addition, due to the fundamental difficulty of estimating depth from monocular RGB images, the output accuracy of these approaches are deficient for high-quality telepresence. Higher depth accuracy can be achieved in a monocular setup by using depth cameras [17]}, although the quality of the results still do not match that of multiview systems.
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